Choosing an Open-Source Annotation Tool in 2026
An honest look at how to pick an open-source data annotation tool, what questions actually narrow the choice, and where Potato fits among Label Studio, Prodigy, Doccano, brat, and Argilla.

News, tutorials, and updates from the Potato team.
An honest look at how to pick an open-source data annotation tool, what questions actually narrow the choice, and where Potato fits among Label Studio, Prodigy, Doccano, brat, and Argilla.





Step-by-step guide to collecting per-step reward signals for PRM training using Potato. Covers first-error mode, per-step annotation, and export to training pipelines.
Tutorial for setting up live coding agent observation with Ollama, Anthropic API, or Claude Agent SDK. Includes pause, rollback, branching, and trajectory export.




Get notified about new tutorials, releases, and community highlights.
Set up multi-criteria rubric evaluation with custom criteria, configurable rating scales, and dimension weights for systematic AI agent evaluation using Potato's rubric_eval.
Potato 2.4.0 ships web agent trace review, real-time live agent evaluation, an LLM chat sidebar, HuggingFace Hub export, webhooks, SSO/OAuth, and five active learning strategies.



Potato 2.2.0 adds 9 new annotation schemas, a pluggable export system, MACE competence estimation, 55 validated survey instruments, and remote data sources.
Potato 2.1.0 brings the instance display system, visual AI support for image and video annotation, span linking, multi-field spans, and layout customization.




Best practices for annotating medical images in Potato, DICOM display, radiology report labeling, adverse event extraction, and IRB-compliant self-hosted deployment.
Configure polygon drawing tools in Potato for image segmentation tasks, with tips for complex shapes, overlapping regions, multi-class polygons, and export to COCO format.




Potato 2.0 ships AI-powered pre-annotation with OpenAI and Claude, multimedia support for audio and video, active learning, bounding box annotation, and a redesigned UI.
Configure AI-powered keyword highlighting in Potato to draw annotator attention to important terms. Covers OpenAI, Claude, and custom keyword list configuration.




Build a pronunciation quality annotation task in Potato with audio playback, waveform visualization, Likert rating scales, and per-recording free-text feedback fields.
Build a speaker identification task in Potato with interactive audio waveforms, timestamp markers, speaker label assignment, and inter-annotator agreement measurement.




Our paper on Potato was accepted at EMNLP 2022. Learn about the research behind the tool and how to cite it in your work.
Best practices for ensuring annotation quality in annotation projects, including practical strategies you can implement with and beyond Potato.




An overview of multi-object tracking annotation concepts and how Potato's video annotation capabilities can support basic tracking workflows.
Create an audio emotion classification task in Potato with interactive waveform display, playback speed controls, Likert scales, and configurable emotion label sets.